A wide variety of drug delivery systems are known to the art, ranging from systems totally relying upon the healthcare professional for dosing decisions and administration to highly automated systems performing one or more tasks such as monitoring, analyzing, dosing decisions and dosing.
At the nonautomated, simplest end of the spectrum, a drug delivery system may comprise a preset regimen performed at a preset infusion rate without feedback, such as when a patient is given a prescribed dosing regimen. At a higher level of control, feedback systems are utilized in which analysis of the patient's current condition is utilized in a feedback controlled manner as input for the dosing analysis. These steps may be performed by the healthcare professional with or without the use of automation or computational tools.
Example of a nomogram based, nonautomated drug delivery system includes various heparin delivery systems now in wide spread use. Other such systems use hirudin, hirulog and other direct thrombin inhibitors. See, e.g., Carr et al., "Glycoprotein IIb/IIIa Blockade Inhibits Platelet-Mediated Force Development and Reduces Gel Elastic Modulus", Thrombosis and Haemostasis, pp 499-505. Heparin is a well known anticoagulant used to avoid clotting, such as during dialysis, thrombolytic therapy, acute unstable angina, cardiac catheterization, coronary artery bypass surgery, stent placement and PTCA, pulmonary embolism, deep vein thrombosis, treatment of transcient ischemic attack and stroke. At certain intervals, blood is drawn from the patient, and analyzed for its coagulation ability. Although heparin is generally viewed as a relative safe and efficacious drug, it may result in an increased risk of hemorrhage, and has proved difficult to select ideal heparin dosage. There is a wide variation in patient-to-patient response, both in the heparin concentration which results from a given heparin infusion rate, and in the patient response to a given heparin concentration. Nonautomated control is difficult and often imprecise.
Various commercially available analysis units are available to analyze a small amount, e.g., a drop, of patient blood to determine the coagulation state of the blood. Based upon this analysis, dosing decisions are made ad hoc or with the aid of a nomogram. The heparin is then administered to the patient based on this decision.
Various proposals have been made to automate the dosing decision step in the heparin delivery. In Dennis R. Mungall, et al., "A Prospective Randomized Comparison of the Accuracy of Computer-Assisted Versus GUSTO Nomogram-directed heparin Therapy", Clinical Pharmacology & Therapeutics, May, 1994, pp 591-596, a computer system utilized the activated partial thromboplastin time (APTT) measured on a preset interval as input to determine dosing decisions. A Bayesian forecasting computer program was utilized, assuming a non-linear pharmacokinetic model for heparin. Initial estimates of heparin requirements were based on prior knowledge of demographic characteristics, specifically weight, sex, and current smoking condition. Similarly, in Kershaw et al., "Computer-Assisted Dosing of heparin, Management With a Pharmacy-Based Anticoagulation Service", Archives of Internal Medicine, May 9, 1994, pp 1005-1011, a computer-assisted dosing of heparin was performed. APTT measurements were used as the input to the system. Finally, specific work has occurred in an attempt to optimize drug delivery where sparse measurements are available. See, e.g., T.C. Jannett et al., "Simulation of Adaptive Control of Anticoagulation During Hemodialysis", Biomedical Applications of Automatic Control, Proceedings from the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Vol. 13, No. 5, 1991, pp 2147-2148.
Various adaptive control systems have been proposed. These systems attempt to utilize data obtained historically and from individual patient response as input to the control system determining drug dosing. These adaptive control systems have particular applicability to delivery systems in which sparse measurements are available. One proposed system by Jannett et al., above, utilizes a model based system with parameter estimation. Sparse measurements, at infrequent or differently timed intervals, are utilized in an attempt to estimate appropriate drug delivery.
At a higher level of integration, various automated drug delivery systems are known to the art. Relatively simple systems utilizing noninvasive monitoring systems monitor a patient variable and provide dosing based upon decisions made by a control system in a feedback controlled manner. For example, automated blood pressure monitoring systems exist. Automated blood pressure measurement devices are automatically activated, typically at preset time intervals, which cause the increase in cuff pressure on an automated blood pressure measurement system, and then the detection of the patient's blood pressure. These systems generally attempt to hold the patient at a preset level, such as a desired blood pressure level, See, e.g., Cosgrove Jr., et al. U.S. Pat. No. 4,280,494, or at a higher level of complexity attempt to mimic the natural variations in a patient's physiologic variable, such as a circadian rhythm in blood pressure. See, e.g., Frucht et al., "Computer-Assisted Blood Pressure Control By Cardiovascular Drugs - Problems in Developing a Closed Loop Control System", Anasth. Intensivther. Notfallmed. 21 (1986).
Yet another noninvasive, feedback controlled system is the GenESA system of Gensia, Inc. which monitors a patient's heart rate as a control input for a system which causes delivery of a exercise simulating agent, such as arbutamine, so as to mimic the effects of aerobic exercise. In one application, such system may be utilized to perform a cardiac stress test on patients, such as by varying the cardiac stress as a function of time. The control of certain physiologic parameters requires the invasive monitoring of the patient, such as in systems requiring direct analysis of the patient's blood. A system from VIA Medical automatically draws and analyzes patient blood. A delivery set is connected to the patient's vein which is utilized for the dual function of fluid delivery, such as a physiologic solution, and blood withdrawal from the patient. A pump is used to draw the blood from the patient through the delivery set. Analysis occurs by drawing the blood through a closed circuit which contains a sensor in-line. Sensors external to the patient measure various analytes in the blood. In suggested operation, the blood drawn from the patient is reinfused to the patient.
Yet another blood analysis system is that shown in Cusack U.S. Pat. No. 5,134,079. A fluid sample collection system utilizes a patient sample, such as blood, with an immiscible fluid, such as air, and a washing fluid, such as saline, to segment portions of the patient sample and to transport them to an analyzer. The blood and saline are connected by a fluid path, which in combination forms a transfer tube to pass the blood and saline alternately to the analyzer. From a fluidics standpoint, the patient sample and the immiscible fluid are input from separate input ports which form a Y-connection with the fluid path towards the analyzer. A third input port forms a T-connection with the fluid path and provides input for the immiscible fluid to the fluid path. A downstream pump causes motion through the fluid path tube. A detector is positioned downstream of the pump but upstream of the output port to the analyzer. In each of the modes of operation described, segmentation of the blood is required. No provision is made for return of the sampled blood to the patient which is not used in the analysis.
Various blood gas measuring systems are known in the art, some of which are noninvasive and some of which are invasive. One such system is made by FOxS Systems which comprises an inter-arterial blood gas system which measures pH, PCO.sub.2, PO.sub.2, and temperature on a continuous basis. The system uses optical fluorescent sensors optimized for each analyte of interest. A system by Diametrics performs blood gas analysis utilizing a small cartridge inserted into the front of an IRMA analyzer. After a calibration step, arterial blood is injected into the cartridge which performs the analysis.
The Biostator.TM. system of Miles Laboratories is an automated, invasive feedback controlled drug delivery system. One line connects the patient in a closed circuit serving to provide fluid delivery, such as saline, to the patient as well as to sample blood from the patient. The sampled blood is then analyzed to determine the glucose concentration, which is used to calculate an insulin infusion rate to control the blood glucose level.
While much progress has been made in the general field of automated, feedback controlled drug delivery, deficiencies remain for certain applications. Current systems for therapeutic dosing are often time consuming, requiring the direct input of a healthcare professional. Automatic analysis is often difficult or impossible and requires substantial skill and training on the part of the healthcare professional. Under such circumstances, it is difficult to perform such therapeutic dosing in a non-hospital environment, such as for in-home healthcare. Further, given the multiple steps and complex nature of the measurement, analysis and dosing steps, errors can occur in any one of these steps and cause a cumulative effect, causing risk for the patient. Further, a high degree of control is often required, especially for administration of anticoagulants, where the therapy has a narrow therapeutic index (i.e., too low a dose will result in decreased efficacy such as reoccurrence of deep vein thrombosis (DVT) and too high a dose will result in side effects (such as bleeding and hemorrhagic stroke). Current practice requires a multiple step operation, with each step incurring the potential for error. Generally, these steps are as follows: the patient is hooked to the heparin IV unit, a bolus of heparin is administered, a sample is drawn and sent to the lab, the lab analyzes the sample for APTT value, the nurse receives the results, with a possible delay of upwards of 1 hour, the heparin dose is determined based on the physician's order or by using a nomogram, the IV pump is adjusted with the new heparin rate and the next sample time is determined. Cumulative errors can result in suboptimal delivery rates.
Despite the numerous attempts to provide a more automated and reliable system for drug delivery, no satisfactory solution has been proposed for systems requiring invasive monitoring of patient blood and subsequent control of anticoagulant effects.
For the delivery of heparin, the rationale for feedback-controlled delivery is based on the following observations:
(1) individual heparin response is variable (a four-fold range in sensitivity and a three-fold range in the rate at which heparin is metabolized/eliminated is not uncommon); PA1 (2) the non-linear dose response curve of individual patients requires frequent titration; PA1 (3) tight control of APTT requires frequent infusion adjustments; PA1 (4) heparin is frequently under-dosed resulting in sub-therapeutic anticoagulation; PA1 (5) over-dosing resulting in excessive bleeding, which can be avoided.
In the current practice of patient management for heparin titration, the following steps have be repeated: a blood sample must be taken and sent to the lab, the clinician must wait for results (with significant turnaround time), a nomogram must be used to calculate a new infusion rate, and the infusion rate on the pump must then be manually adjusted. The potential for error across these steps can be minimized and the effort required by nursing staff greatly reduced by the use of an automated system.